The present invention disclosed herein relates to a scientific English teaching method, and more particularly, to a playing technology for intentionally stimulating the brain structure including the optical nerves, through changing English graphic patterns.
(Background 1. ) Professor Noam Chomsky, the founder of Transformational-Generative Grammar, explains in his book on Universal Grammar, which pertains to cognitive grammar, that all grammar and sentences made from grammar are psychological products of the brain that can only be subject to the principle of 3-dimensional spatial cognition of the brain, and that this principle involves 3 major types of forces: merge (merging of divided content), piping (connecting related elements), and moving (interconnections between a subject and meanings associated with the subject).
That is, all sentences have a backbone or structure core in their sentence structures, and evolve or vary into diverse sentence patterns based on the 3 forces described above. Prof. Noam Chomsky has defined this into a single principle, a minimized technique of minimalism, a grammar through which sentences can be categorized into a 5 sentence structure pattern, a 28 sentence structure pattern, a 108 sentence structure pattern, and so forth.
(Background 2. ) Due to advances in artificial intelligence design technology, language recognition programs and automated translation programs currently have the same extraction capabilities as humans, and surpass human ability in terms of high volume/high speed search, and have abstract concept cognition and assembling capabilities that are surpassing those of humans.
Automated translation tools provided by Google and other large websites are able to almost perfectly translate sentences that have been fragmented into segments, and can translate most sequential, specific, and frequently used sentences containing machine-stored meanings very smoothly.
While sentences that contain abstract meanings, are non-sequential and non-specific, and are not frequently used cannot be said to be completely machine translatable, this cannot be attributed to the problems of current translation programs, but rather, can be attributed to limitations associated with term databases employed by modern society search robots or translation robots and the developed state of artificial intelligence that learns from the same (often limitations that may be financial or administrative cause-related). For example, at present, even if a supplemental polishing task by a person is needed in order to achieve a proper translation in a certain field, if language data in the relevant field were to be additionally stored and learned, and an improved version of an automated translation machine is used, sentences that are complex and have technical content in the field could be readily and capably translated.
This reality attests to the exceptional potential of sentence recognition and translation programs that are realized by language databases and artificial intelligence referring to the same, which systematically categorize and store extremely diverse sentences extracted from the vast sea of languages found on the internet, and vast amounts of words and phrases discovered by scholars.
(Background 3. ) Language processing tools such as word programs and animation graphics technology have developed at remarkable speed, due to the increase in computer storage/calculation capability and the processing speeds of display devices which display such programs. While in the past, most sentence processing programs have been restricted by storage capacity per character and expressing speed so as to convert and process character data in formulaic and rigid formats, recent word programs are showing their ability to demolish the barrier between characters and drawings. For example, various presentation-related file formats that use the animating gif file format or flash format, and macro functions are able to express characters as animated moving images through simple tools on even the everyday PC.